scholarly journals Zika Virus Prediction Using AI-Driven Technology and Hybrid Optimization Algorithm in Healthcare

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Pankaj Dadheech ◽  
Abolfazl Mehbodniya ◽  
Shivam Tiwari ◽  
Sarvesh Kumar ◽  
Pooja Singh ◽  
...  
Keyword(s):  
Public Health ◽  
Optimization Algorithm ◽  
Zika Virus ◽  
Health Hazard ◽  
Data Encryption ◽  
Machine Learning Algorithms ◽  
Hybrid Optimization ◽  
Infection Frequency ◽  
Optimization Strategy ◽  
Hybrid Optimization Algorithm

The Zika virus presents an extraordinary public health hazard after spreading from Brazil to the Americas. In the absence of credible forecasts of the outbreak's geographic scope and infection frequency, international public health agencies were unable to plan and allocate surveillance resources efficiently. An RNA test will be done on the subjects if they are found to be infected with Zika virus. By training the specified characteristics, the suggested Hybrid Optimization Algorithm such as multilayer perceptron with probabilistic optimization strategy gives forth a greater accuracy rate. The MATLAB program incorporates numerous machine learning algorithms and artificial intelligence methodologies. It reduces forecast time while retaining excellent accuracy. The projected classes are encrypted and sent to patients. The Advanced Encryption Standard (AES) and TRIPLE Data Encryption Standard (TEDS) are combined to make this possible (DES). The experimental outcomes improve the accuracy of patient results communication. Cryptosystem processing acquires minimal timing of 0.15 s with 91.25 percent accuracy.

Optimization Design of Drawbead in Drawing Tools of Autobody Cover Panel

2002 ◽  
Vol 124 (2) ◽  
pp. 278-285 ◽  
Author(s):  
Gang Liu ◽  
Zhongqin Lin ◽  
Youxia Bao
Keyword(s):  
Optimization Algorithm ◽  
Optimization Design ◽  
Design Method ◽  
Experimental Results ◽  
Hybrid Optimization ◽  
Force Model ◽  
Hybrid Optimization Algorithm ◽  
Design Plan ◽  
Formed Part ◽  
Restraining Force

In the tooling design of autobody cover panels, design of drawbead will affect the distribution of drawing restraining force along mouth of dies and the relative flowing velocity of the blank, and consequently, will affect the distributions of strain and thickness in a formed part. Therefore, reasonable design of drawbead is the key point of cover panels’ forming quality. An optimization design method of drawbead, using one improved hybrid optimization algorithm combined with FEM software, is proposed in this paper. First, we used this method to design the distribution of drawbead restraining force along the mouth of a die, then the actual type and geometrical parameters of drawbead could be obtained according to an improved drawbead restraining force model and the improved hybrid optimization algorithm. This optimization method of drawbead was used in designing drawing tools of an actual autobody cover panel, and an optimized drawbead design plan has been obtained, by which deformation redundancy was increased from 0% under uniform drawbead control to 10%. Plastic strain of all area of formed part was larger than 2% and the minimum flange width was larger than 10 mm. Therefore, not only better formability and high dent resistance were obtained, but also fine cutting contour line and high assembly quality could be obtained. An actual drawing part has been formed using the optimized drawbead, and the experimental results were compared with the simulating results in order to verify the validity of the optimized design plan. Good agreement of thickness on critical areas between experimental results and simulation results proves that the optimization design method of drawbead could be successfully applied in designing actual tools of autobody cover panels.

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